Mattermost announces AI-Enhanced Secure Collaboration Platform to enable both innovation and data control for government and technology organizations

Because while they stall, their more innovative counterparts will leapfrog ahead in efficiency, cost-savings, and citizen satisfaction. Imagine having the option to renew your license just by having a conversation, applying for medical benefits, inquiring about upcoming road or school closures, or even requesting your city take care of the dying tree on your street. Or, if there’s a storm and a downed powerline near you, AI can send targeted notifications to all the area residents to avoid potentially dangerous situations. Remember when ChatGPT exploded onto the scene and showed us how useful conversational AI could be?

EMMA guides around one million applicants per month regarding the various services offered by the department and directs them to relevant pages and resources. AI-based cognitive automation, such as rule-based systems, speech recognition, machine translation, and computer vision, can potentially automate government tasks at unprecedented speed, scale, and volume. A Governing magazine report found that 53% of local government officials cannot complete their work on time due to low operational efficiencies like manual paperwork, data collection, and reporting. As a result, their task backlogs keep piling up, causing further delays in government workflows. In the UK, National Health Service (NHS) formed an initiative to collect data related to COVID patients to develop a better understanding of the virus.

GAO Report: Federal Agencies Are Not Complying with AI Requirements

One major challenge is ensuring that the data is transmitted securely between different government agencies and stakeholders. With so many parties involved in managing and analyzing government data, it’s essential to have a secure, private connection that can ensure the confidentiality and integrity of the data as it’s shared. However, establishing and maintaining such connections can be a complex and costly process, especially as the volume of data being transmitted continues to grow. To prepare the data stored in these lakes for analysis and use, data scientists and analysts need It can automate crucial processes like records management and ensure that tasks are carried out in compliance with industry governance protocols and standards and can restrict access to sensitive data in an organization.

That comes with the ability to create a storage infrastructure–or even create their own private cloud – that can be used going forward like a private cloud for each agency. The circuit itself can be created in less than eight hours, which allows for substantial changes to the system essentially by the end of a business day. Once established, the secure cloud fabric becomes the support infrastructure for cloud migration and cloud portability. “Agencies can have the ability to move workloads between clouds easily, as well as having the ability to manage their Docker or Kubernetes environment in a simple structured environment.

How viAct empowers Government Administration?

As a result, traditional cybersecurity policies and defense can be applied to protect against some AI attacks. While AI attacks can certainly be crafted without accompanying cyberattacks, strong traditional cyber defenses will increase the difficulty of crafting certain attacks. The US government generates and collects a massive amount of data each year – everything from census information to intelligence gathering.

This kind of multilayered approach (regulating the development, deployment, and use of AI technologies) is how we deal with most safety-critical technologies. In aviation, the Federal Aviation Administration gives its approval before a new airplane is put in the sky, while there are also rules for who can fly the planes, how they should be maintained, how the passengers should behave, and where planes can land. The council will develop recommendations for its utilization of artificial intelligence throughout state government, while honoring transparency, privacy and equity. Those recommendations should be ready by no later than six months from the date of its first convening. A final recommended action plan should be ready no later than 12 months from its first convening. Because AI systems have already been deployed in critical areas, stakeholders and appropriate regulatory agencies should also retroactively apply these suitability tests to already deployed systems.

If health research industries train a model on data that’s biased – for instance, does not include any data from Native American populations – then it’s not going to produce equitable results. Department of Energy has developed an AI tool called Transportation State Estimation Capability (TranSEC). It uses machine learning to analyze traffic flow, even from incomplete or sparse traffic data, to deliver real-time street-level estimations of vehicle movements. A highly regulated approach to AI development, like in the European model, could help to keep people safe, but it could also hinder innovation in countries that accept the new standard, something EU officials have said they want in place by the end of the year. That is why many industry leaders are urging Congress to adopt a lighter touch when it comes to AI regulations in the United States.

Our research shows, however, that the role countries are likely to assume in decarbonized energy systems will be based not only on their resource endowment but also on their policy choices. Government to identify, assess, test and implement technologies against the problems of foreign propaganda and disinformation, in cooperation with foreign partners, private industry and academia. Additionally, conversational AI offers to revolutionize the operations and missions of all public sector agencies. Conversational AI is a type of artificial intelligence intended to facilitate smooth voice or text communication between people and computers.

Safe AI content for governments

The report shall include a discussion of issues that may hinder the effective use of AI in research and practices needed to ensure that AI is used responsibly for research. The Assistant to the President for National Security Affairs and the Director of OSTP shall coordinate the process of reviewing such funding requirements to facilitate consistency in implementation of the framework across funding agencies. (ii)   Within 150 days of the date of this order, the Secretary of the Treasury shall issue a public report on best practices for financial institutions to manage AI-specific cybersecurity risks. (t)  The term “machine learning” means a set of techniques that can be used to train AI algorithms to improve performance at a task based on data. Additionally, the IBM Cloud Security and Compliance Center is designed to deliver enhanced cloud security posture management (CSPM), workload protection (CWPP), and infrastructure entitlement management (CIEM) to help protect hybrid, multicloud environments and workloads. The workload protection capabilities aim to prioritize vulnerability management to support quick identification and remediation of critical vulnerabilities.

Because the users’ data never leaves their devices, their privacy is protected and their fears that companies may misuse their data once collected are allayed. Federated learning is being looked to as a potentially groundbreaking solution to complex public policy problems surrounding user privacy and data, as it allows companies to still analyze and utilize user data without ever needing to collect that data. Public policy creating “AI Security Compliance” programs will reduce the risk of attacks on AI systems and lower the impact of successful attacks. Compliance programs would accomplish this by encouraging stakeholders to adopt a set of best practices in securing systems against AI attacks, including considering attack risks and surfaces when deploying AI systems, adopting IT-reforms to make attacks difficult to execute, and creating attack response plans. This program is modeled on existing compliance programs in other industries, such as PCI compliance for securing payment transactions, and would be implemented by appropriate regulatory bodies for their relevant constituents. Biden’s executive order introduces new reporting requirements for organizations that develop (or demonstrate an intent to develop) foundational models.

The New CAIO: Proposed Memorandum for the Heads of Executive Departments and Agencies

Today’s most capable AI systems use nearly 2 million times the computational power used 10 years ago. Concurrently, the AI industry has moved toward more general models, capable of engaging in a wide range of tasks. Previous models focused on a specific modality, such as vision, and tended to be specialized in particular tasks.

SAIF ensures that ML-powered applications are developed in a responsible manner, taking into account the evolving threat landscape and user expectations. We’re excited to share the first steps in our journey to build a SAIF ecosystem across governments, businesses and organizations to advance a framework for secure AI deployment that works for all. The guidelines shall, at a minimum, describe the significant factors that bear on differential-privacy safeguards and common risks to realizing differential privacy in practice.

Faster training of AI modules with high on ground accuracy

Read more about Secure and Compliant AI for Governments here.